Method of providing dynamic speech processing services during variable network connectivity

ABSTRACT

A user device provides dynamic speech processing services during variable network connectivity with a network server. The user device includes a connection determiner that monitors a level of network connectivity between the user device and the network server, a simplified speech processor that processes speech data and is initiated based on a determination by the connection determiner that the level of network connectivity between the user device and the network server is impaired, a memory that stores processed speech data processed by the simplified speech processor, and a transmitter configured to transmit the stored processed speech data. The connection determiner determines when the level of network connectivity between the user device and the network server is no longer impaired.

CROSS-REFERENCE

This application is a continuation of U.S. patent application Ser. No.13/403,495, filed on Feb. 23, 2012, which is a continuation of U.S.patent application Ser. No. 12/329,716, filed on Dec. 8, 2008, now U.S.Pat. No. 8,150,696, the disclosures of which are expressly incorporatedherein by reference in its entireties.

BACKGROUND

1. Field of the Disclosure

The present disclosure relates to the field of communications. Moreparticularly, the present disclosure relates to providing dynamic speechprocessing services during variable network connectivity.

2. Background Information

Some client devices are connected to network servers. These networkservers often have speech processing capabilities, performed by speechprocessors instantiated on network servers. However, when the networkconnection is compromised and the connection to a network server is lostor impaired, client devices that are connected to the network serversare unable to perform speech processing.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an exemplary general computer system that includes a set ofinstructions for providing dynamic speech processing services duringvariable network connectivity;

FIG. 2 illustrates an exemplary network connection between a clientdevice and a network server, according to an aspect of the presentdisclosure;

FIG. 3 is a flowchart depicting an exemplary process of providingdynamic speech processing services during variable network connectivity,according to an aspect of the present disclosure; and

FIG. 4 illustrates an exemplary client device, according to an aspect ofthe present disclosure.

DETAILED DESCRIPTION

In view of the foregoing, the present disclosure, through one or more ofits various aspects, embodiments and/or specific features orsub-components, is thus intended to bring out one or more of theadvantages as specifically noted below.

According to an aspect of the present disclosure, a client device forproviding dynamic speech processing services during variable networkconnectivity with a network server includes a connection determiner thatdetermines the level of network connectivity of the client device andthe network server; a simplified speech processor that processes speechdata that is initiated based on the determination from the connectiondeterminer that the network connectivity is impaired or unavailable; aspeech data storage that stores processed speech data from thesimplified speech processor; and a transition unit that determines whento transmit the stored speech data and connects with the network server,based on the determination of the connection determiner.

In another aspect of the present disclosure, the transition unittransmits a request to the network server to reinitiate an extendedspeech processor of the network server, when the simplified speechprocessor of the client device has no pending transactions. Pendingtransactions include transactions wherein the speech processor isreceiving speech data from a user or processing speech data.

In an aspect of the present disclosure, the simplified speech processorof the client device uses less processing power than the extended speechprocessor of the network server.

In another aspect of the present disclosure, a conservation user inputthat allow users to initiate the simplified speech processor.

In an aspect of the present disclosure, the simplified speech processoroutputs a predetermined prompt to collect user input.

In yet another aspect of the present disclosure, the connectiondeterminer categorizes the level of network connectivity of the clientdevice and the network server, and the simplified speech processorselects one of a plurality of speech processing engines, based on thecategorization of the connection determiner.

According to an aspect of the present disclosure, a method for providingdynamic speech processing services during variable network connectivitywith a network server includes determining, at a client device, thelevel of network connectivity between the client device and the networkserver; initiating a simplified speech processor that processes speechdata, based on the determination that the network connectivity isimpaired or unavailable; storing processed speech data from thesimplified speech processor; determining when to transmit the storedspeech data; and connecting with the network server, based on thedetermination of the level of network connectivity.

In an aspect of the present disclosure, the method includes transmittinga request to the network server to reinitiate an extended speechprocessor of the network server, when the simplified speech processor ofthe client device has no pending transactions. Pending transactionsinclude transactions wherein the simplified speech processor isreceiving speech data from a user or the simplified speech processor isprocessing speech data.

In another aspect of the present disclosure, the simplified speechprocessor uses less processing power than the extended speech processorof the network server.

In an aspect of the present disclosure, the method includes receivinguser input that initiates the simplified speech processor.

In another aspect of the present disclosure, the simplified speechprocessor outputs a predetermined prompt to collect user input.

In yet another aspect of the present disclosure, the method includescategorizing the level of network connectivity of the client device andthe network server, and selecting one of a plurality of speechprocessing engines, based on the categorization of the connectiondeterminer.

According to an aspect of the present disclosure, a tangible computerreadable medium storing a program for providing dynamic speechprocessing services during variable network connectivity with a networkserver includes a connection determining code segment executable todetermine the level of network connectivity of the client device and thenetwork server; a simplified speech processing code segment executableto process speech data and is initiated based on the determination fromthe connection determining code segment that the network connectivity isimpaired or unavailable; a speech data storage code segment executableto store processed speech data from the simplified speech processingcode segment; and a transition code segment executable to determine whento transmit the stored speech data and connects with the network server,based on the determination of the connection determining code segment.

In an aspect of the present disclosure, the transition code segmenttransmits a request to the network server to reinitiate an extendedspeech processing code segment of the network server, when thesimplified speech processing code segment of the client device has nopending transactions. Pending transactions include transactions whereinthe simplified speech processor is receiving speech data from a user orthe simplified speech processor is processing speech data.

In another aspect of the present disclosure, the simplified speechprocessing code segment uses less processing power than the extendedspeech processing code segment of the network server.

In an aspect of the present disclosure, the computer readable mediumincludes a conservation code segment that allow users to initiate thesimplified speech processor.

In another aspect of the present disclosure, the simplified speechprocessing code segment outputs a predetermined prompt to collect userinput.

In yet another aspect of the present disclosure, the connectiondetermining code segment categorizes the level of network connectivityof the client device and the network server, and the simplified speechprocessing code segment selects one of a plurality of speech processingengines, based on the categorization of the connection determining codesegment.

FIG. 1 is an illustrative embodiment of a general computer system, onwhich a method to provide dynamic speech processing services duringvariable network connectivity can be implemented, which is shown and isdesignated 100. The computer system 100 can include a set ofinstructions that can be executed to cause the computer system 100 toperform any one or more of the methods or computer based functionsdisclosed herein. The computer system 100 may operate as a standalonedevice or may be connected, for example, using a network 126, to othercomputer systems or peripheral devices.

In a networked deployment, the computer system may operate in thecapacity of a server or as a client user computer in a server-clientuser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 100 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a global positioning satellite(GPS) device, a palmtop computer, a laptop computer, a desktop computer,a communications device, a wireless telephone, a land-line telephone, acontrol system, a camera, a scanner, a facsimile machine, a printer, apager, a personal trusted device, a web appliance, a network router,switch or bridge, or any other machine capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that machine. In a particular embodiment, the computer system 100 canbe implemented using electronic devices that provide voice, video ordata communication. Further, while a single computer system 100 isillustrated, the term “system” shall also be taken to include anycollection of systems or sub-systems that individually or jointlyexecute a set, or multiple sets, of instructions to perform one or morecomputer functions.

As illustrated in FIG. 1, the computer system 100 may include aprocessor 102, for example, a central processing unit (CPU), a graphicsprocessing unit (GPU), or both. Moreover, the computer system 100 caninclude a main memory 104 and a static memory 106 that can communicatewith each other via a bus 108. As shown, the computer system 100 mayfurther include a video display unit 110, such as a liquid crystaldisplay (LCD), an organic light emitting diode (OLED), a flat paneldisplay, a solid state display, or a cathode ray tube (CRT).Additionally, the computer system 100 may include an input device 112,such as a keyboard, and a cursor control device 114, such as a mouse.The computer system 100 can also include a disk drive unit 116, a signalgeneration device 118, such as a speaker or remote control, and anetwork interface device 120.

In a particular embodiment, as depicted in FIG. 1, the disk drive unit116 may include a computer-readable medium 122 in which one or more setsof instructions 124, e.g. software, can be embedded. A computer-readablemedium 122 is a tangible article of manufacture, from which sets ofinstructions 124 can be read. Further, the instructions 124 may embodyone or more of the methods or logic as described herein. In a particularembodiment, the instructions 124 may reside completely, or at leastpartially, within the main memory 104, the static memory 106, and/orwithin the processor 102 during execution by the computer system 100.The main memory 104 and the processor 102 also may includecomputer-readable media.

In an alternative embodiment, dedicated hardware implementations, suchas application specific integrated circuits, programmable logic arraysand other hardware devices, can be constructed to implement one or moreof the methods described herein. Applications that may include theapparatus and systems of various embodiments can broadly include avariety of electronic and computer systems. One or more embodimentsdescribed herein may implement functions using two or more specificinterconnected hardware modules or devices with related control and datasignals that can be communicated between and through the modules, or asportions of an application-specific integrated circuit. Accordingly, thepresent system encompasses software, firmware, and hardwareimplementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

The present disclosure contemplates a computer-readable medium 122 thatincludes instructions 124 or receives and executes instructions 124responsive to a propagated signal, so that a device connected to anetwork 126 can communicate voice, video or data over the network 126.Further, the instructions 124 may be transmitted or received over thenetwork 101 via the network interface device 120.

FIG. 2 illustrates an exemplary network connection between a clientdevice and a network server, according to an aspect of the presentdisclosure. Various types of client devices use speech processingservices via network servers, including cell phones, personal digitalassistants, MP3 players, satellite radio systems, etc. In FIG. 2,exemplary client devices 201 may be used by users in an analog, digital,or IP telephone network systems. Thus, the network system may be apublic switched telephone network (PSTN), a cellular telephone network,a digital telephone network system, a voice over internet protocol(VoIP) telephony network system, or any other audible communicationnetwork.

In the exemplary architecture in FIG. 2, user devices 201 and 202 areconnected to a network communication node, e.g., network server 204.User devices 201/202 may be connected to network server 204 via one ormultiple networks, e.g., networks 203. It is understood that the networkcommunication node may be implemented in any data network(s) accessibleby the users, including (but not limited to) wide area networks (WANs),PSTNs, and the internet (using, e.g., voice over internet protocol),without departing from the spirit and scope of the present disclosure.

In an exemplary embodiment, user device 201 or 202 determines the levelof network connectivity of user device 201/202 and network server 204.When user device 201/202 determines that network connectivity isimpaired or unavailable, a simplified speech processor, which is storedon the user device 201/202, is initiated. Then, user device 201/202stores the processed speech data, including information on all decisionsmade and which dialog paths are taken, from the simplified speechprocessor. Furthermore, when the user device 201/202 determines that thenetwork connectivity is no longer impaired, user device 201/202transmits a message to network server 204, instructing network server204 to reinitiate the speech processor, stored on network server 204.

FIG. 3 is a flowchart depicting an exemplary process for providingdynamic speech processing services during variable network connectivity,according to an aspect of the present disclosure. During normalconnectivity between the network server and the client device, theclient devices utilizes speech processing engines stored in the networkserver. In step S301, a connection determiner (which includes hardwareand/or software elements) of the client device constantly monitors theconnection between the network server and the client device. In oneembodiment, the connection is monitored at predetermined intervals,e.g., every 20 milliseconds. In step S302, the connection determinerdetermines whether the network connection has been impaired orunavailable for a predetermined period of time, e.g., for five seconds.

In another embodiment, the connection determiner categorizes orquantifies the level of connectivity between the network server and theclient device. For example, the connection determiner assignspredetermined values (e.g., from 1 to 5 with one being the poorestconnectivity and 5 being the best connectivity) to predetermined rangesof data transfer rates. For example, the connection determiner mayassign a value of 5 to a data transfer rate of 1.0 mbps or higher.

If the network connection has been impaired or is unavailable for thispredetermined period of time, then the client device initiates asimplified speech processor (which includes hardware and/or softwareelements) stored on the client device in step S303. In one embodiment,this simplified speech processor does not rely upon the speechprocessing of the network server, and uses less computing power comparedto the extended or non-simplified speech processors stored in thenetwork server. Therefore, when network connectivity is impaired orunavailable, the client device is capable of utilizing automatic speechrecognition (ASR) or other speech processing engines. At a minimum,automatic speech recognition (ASR) or speech processing engines arebeing used to recognize and process spoken words, converting the spokenwords to machine-readable input. Examples of conventional automaticspeech recognition or speech processing engines include (but are notlimited to) speech recognition software, such as CMU Sphinx, HiddenMarkov Model Toolkit (HTK), VoxForge, Xvoice, Open Mind Speech,GnomeVoiceControl, CSLU Toolkit, IBM ViaVoice, and Microsoft Speech API.

Other speech processing engines include text-to-speech (TTS) synthesisengines, dialog manager (DM), natural language understanding (NLU)engines, and language generation (LG) engines. Examples of TTS enginesinclude Nuance Specify and AT&T's Natural Voices. These engines convertmachine-stored text into speech. NLU engines, such as, for example,AT&T's Watson NLU, extract meaning (e.g., an action item) frommachine-readable text. Dialog manager engines are responsible forproviding back-office services, such as database access (e.g., lookingup account balances), and also keep track of the state of the dialogbetween the automated system and the user (e.g., judging whether a userspeech input was misrecognized and whether a re-prompt is needed ornot). Dialog manager engines also determine the next step to take in thedialog. Finally, an LG engine generates written text, such as the nextdialog prompt to be synthesized by the TTS engine and output to theuser, from intent information (for example, a prompt asking for accountnumber).

Simultaneously, in step S304, the client device continually checks theconnection with the network server (e.g., by sending “keep alive”messages to the network server), attempting to reconnect with thenetwork server.

In one aspect of the present disclosure, the simplified speech processorof the client device provides a simplified speech processing engine,which uses less computing power than the speech processor stored in thenetwork server. In one embodiment, this simplified speech processingengine may be a simple machine directed speech-enabled processor. Thesimplified machine-directed speech-enabled processor providespredetermined prompts to the user, which may be voice prompts or textprompts displayed on a screen, or may be generated by a TTS engine. Thesimplified machine-directed speech processing contrasts with anyserver-based, mixed-initiative dialog system that contains many, if notall, of the different kinds of speech engines discussed above.

For example, a user may choose to instruct the client device to record aparticular TV program on a remote DVR device at a particular time. Thesimplified machine-directed speech processor would first prompt the userto indicate what operation the user wishes to be performed. For example,the speech process may output an audible prompt, such as “Select Action”or “What action would you like performed?”. The user's spoken responseto the prompt may be, for example, “Record Program”, “DVR”, etc.

Using conventional speech recognition software, the simplifiedmachine-directed speech processor will then recognize and process thespeech input or speech data. Based on this processed speech data, thespeech processor will output additional prompts to the user. Forexample, after the user indicates the action “Record TV program”, thespeech processor may output the prompt “What TV program?” or “What TVprogram do you wish to record?”. Based on this process speech data, thespeech processor may output additional prompts, such as “What Time?” or“What Day of the Week?”. This kind of simplified speech processingparadigm contrasts with any more sophisticated processing possible onmore powerful network servers. For example, a sophisticated or extendednatural-language speech recognition engine, running on a network server,would be capable of correctly interpreting the spoken command “RecordDesperate Housewives next Sunday”.

In another aspect of the present disclosure, the speech processor mayselect and utilize one of a plurality of speech processing engines,based on the quantified level of connectivity between the network serverand the client device, as discussed above. Thus, if the quantified levelof connection between the network server and the client device is thelowest quantified value (e.g., 1 out of a range from 1 to 5), then thespeech processor will select a speech processing engine, which uses theleast computing power. For example, the speech processor may use alocal, device-based speech processing engine that uses amachine-directed speech-enabled engine that outputs speech or textprompts (as discussed above).

In one aspect of the present disclosure, this simplified speechprocessor may provide a prompt that includes a numbered list of possibleoperations. This prompt may be a an audible representation or textdisplayed on the screen of the client device. In response to the prompt,the user may say the predetermined selection provided in the prompt orthe number associated with one of the predetermined selections providedin the prompt. In contrast, if the quantified level of connectionbetween the network server is higher (e.g., 3 out of a range of 1 to 5),the speech processor will select and utilize a speech processing enginethat uses more computing power. In this instance, the speech processormay also partially rely on computing power from the network server.

In step S305, after the speech processor of the client device processesthe user's speech data or speech input, a speech data storage (whichincludes hardware and/or software elements) stores or caches theprocessed speech data. In step S306, the connection determinerdetermines that the connection between the network server and the clienthas been re-established or the quantified level of connectivity hasreached a predetermined threshold. Therefore, in step S306, theconnection between the network server and the client device isre-established. Then, in step S307, a transition unit (which includeshardware and/or software elements) determines when to reinitiate thespeech processor of the network server. Specifically, the transitionunit determines if there is a pending transaction being performed by thespeech processor of the client device. For example, the transition unitdetermines if the speech processor is in the process of receiving speechdata from the user or determines whether speech data is being processed.

Then, in step S308, the transition unit reinitiates the speech processorof the network server, based on step S207. In step S308, the transitionunit also transmits the stored speech data in the speech data storage.In another embodiment, stored speech data can be transmitted to theuser, when the connection determiner determines that the networkconnection has been re-established or when the connectivity level issufficient to facilitate transmission of the speech data.

FIG. 4 illustrates an exemplary client device 201, according to anaspect of the present disclosure. As discussed above, FIG. 4 illustratesexemplary components (which include hardware and/or software elements)of client device 201, including connection determiner 401, simplifiedspeech processor 402, speech data storage 403, and transition unit 404.Speech determiner 401 determines the level of network connectivity ofthe client device and the network server. Simplified speech processor402 processes speech data and is initiated based on the determinationfrom the connection determiner that the network connectivity is impairedor unavailable. Speech data storage 403 stores processed speech datafrom the simplified speech processor; and transition unit 404 determineswhen to transmit the stored speech data and connects with the networkserver, based on the determination of the connection determiner.

Accordingly, the present disclosure enables dynamic speech processingservices during variable network connectivity by client devices usingsimplified speech processors. The present disclosure also enablesseamless re-initiation of network-based speech processors, when thenetwork connection has been re-established.

Although the invention has been described with reference to severalexemplary embodiments, it is understood that the words that have beenused are words of description and illustration, rather than words oflimitation. Changes may be made within the purview of the appendedclaims, as presently stated and as amended, without departing from thescope and spirit of the invention in its aspects. Although the inventionhas been described with reference to particular means, materials andembodiments, the invention is not intended to be limited to theparticulars disclosed; rather the invention extends to all functionallyequivalent structures, methods, and uses such as are within the scope ofthe appended claims.

For example, the present disclosure may be implemented to control andconserve computing power and energy. For example, the present disclosemay also comprise an energy or computing power conservation setting,which the user may turn on and off, which initiates the simplifiedspeech processor. Furthermore, this energy or computing powerconservation setting may include a range of settings, which eachcorresponds to a plurality of simplified speech processing engines. Forexample, the user may select conservation settings ranging from 1 to 5,wherein setting “1” uses the least energy and computer power and setting“5” uses the most energy and computer power. Based on the settingselected by the user, the speech process will select one of a pluralityof speech processing engines that use a variety of levels of computerpower, as discussed above.

While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. Accordingly, the disclosure is considered to include anycomputer-readable medium or other equivalents and successor media, inwhich data or instructions may be stored.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the disclosure is not limited tosuch standards and protocols. For example, standards for Internet andother packed switched network transmission standards and protocols forthe Internet and other packet switched network transmission, e.g., SRGS(Speech Recognition Grammar Specification), SISR (SemanticInterpretation for Speech Recognition), SSML (Speech Synthesis MarkupLanguage), PLS (Pronunciation Lexicon Specification), CCXML (CallControl Extensible Markup Language), represent examples of the state ofthe art. Such standards are periodically superseded by faster or moreefficient equivalents having essentially the same functions.Accordingly, replacement standards and protocols having the same orsimilar functions are considered equivalents thereof.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R.§1.72(b) and is submitted with the understanding that it will not beused to interpret or limit the scope or meaning of the claims. Inaddition, in the foregoing Detailed Description, various features may begrouped together or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

The above disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover all suchmodifications, enhancements, and other embodiments which fall within thetrue spirit and scope of the present disclosure. Thus, to the maximumextent allowed by law, the scope of the present disclosure is to bedetermined by the broadest permissible interpretation of the followingclaims and their equivalents, and shall not be restricted or limited bythe foregoing detailed description.

1-20. (canceled)
 21. A user device for providing dynamic speech processing services during variable network connectivity with a network server, comprising: a connection determiner that monitors a level of network connectivity between the user device and the network server; a simplified speech processor that processes speech data and is initiated based on a determination by the connection determiner that the level of network connectivity between the user device and the network server is impaired; a memory that stores processed speech data processed by the simplified speech processor; and a transmitter configured to transmit the stored processed speech data, wherein the connection determiner determines when the level of network connectivity between the user device and the network server is no longer impaired.
 22. The user device according to claim 21, wherein a request is transmitted from the user device to reinitiate a non-simplified speech processor of the network server to seamlessly reinitiate the non-simplified speech processor, in response to a determination by the connection determiner that the level of network connectivity between the user device and the network server is no longer impaired.
 23. The user device according to claim 22, wherein the simplified speech processor of the user device uses less computing power than the non-simplified speech processor of the network server.
 24. The user device according to claim 22, wherein the request to reinitiate the non-simplified speech processor is transmitted during a time when the simplified speech processor is not processing speech data.
 25. The user device according to claim 21, wherein the connection determiner categorizes the level of network connectivity between the user device and the network server.
 26. The user device according to claim 21, wherein the simplified speech processor selects one of a plurality of speech processing engines based upon a quantified level of network connectivity between the user device and the network server.
 27. The user device according to claim 21, wherein the simplified speech processor selects one of a plurality of speech processing engines, based on a computing power level of each of the speech processing engines.
 28. A method for providing dynamic speech processing services during variable network connectivity with a network server, comprising: monitoring, at a user device, a level of network connectivity between the user device and the network server; initiating a simplified speech processor that processes speech data, based on a determination that the level of network connectivity between the user device and the network server is impaired; storing processed speech data processed by the simplified speech processor; determining when the level of connectivity between the user device and the network server is no longer impaired; and transmitting the stored processed speech data.
 29. The method according to claim 28, further comprising: transmitting a request to reinitiate a non-simplified speech processor of the network server to seamlessly reinitiate the non-simplified speech processor, in response to a determination that the level of network connectivity between the user device and the network server is no longer impaired.
 30. The method according to claim 29, wherein the simplified speech processor of the user device uses less computing power than the non-simplified speech processor of the network server.
 31. The method according to claim 29, wherein the request to reinitiate the non-simplified speech processor is transmitted during a time when the simplified speech processor is not processing speech data.
 32. The method according to claim 28, further comprising: categorizing the level of network connectivity between the user device and the network server.
 33. The method according to claim 28, further comprising: selecting one of a plurality of speech processing engines based upon a quantified level of network connectivity between the user device and the network server.
 34. The method according to claim 28, further comprising: selecting one of a plurality of speech processing engines, based on a computing power level of each of the speech processing engines.
 35. A non-transitory computer readable storage medium encoded with an executable computer program for providing dynamic speech processing services during variable network connectivity with a network server and that, when executed by a processor, causes the processor to perform operations comprising: monitoring, at a user device, a level of network connectivity between the user device and the network server; initiating a simplified speech processor that processes speech data, based on a determination that the level of network connectivity between the user device and the network server is impaired; storing processed speech data processed by the simplified speech processor; determining when the level of connectivity between the user device and the network server is no longer impaired; and transmitting the stored processed speech data.
 36. The non-transitory computer readable storage medium according to claim 35, transmitting a request to reinitiate a non-simplified speech processor of the network server to seamlessly reinitiate the non-simplified speech processor, in response to a determination that the level of network connectivity between the user device and the network server is no longer impaired.
 37. The non-transitory computer readable storage medium according to claim 36, wherein the simplified speech processor of the user device uses less computing power than the non-simplified speech processor of the network server.
 38. The non-transitory computer readable storage medium according to claim 36, wherein the request to reinitiate the non-simplified speech processor is transmitted during a time when the simplified speech processor is not processing speech data.
 39. The non-transitory computer readable storage medium according to claim 35, further comprising: categorizing the level of network connectivity between the user device and the network server.
 40. The non-transitory computer readable storage medium according to claim 35, further comprising: selecting one of a plurality of speech processing engines, based on a computing power level of each of the speech processing engines. 